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gauseR: Simple methods for fitting Lotka‐Volterra models describing Gause’s “Struggle for Existence”

Point 1: The ecological models of Alfred J. Lotka and Vito Volterra have had an enormous impact on ecology over the past century. Some of the earliest—and clearest—experimental tests of these models were famously conducted by Georgy Gause in the 1930s. Although well known, the data from these experi...

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Autores principales: Mühlbauer, Lina K., Schulze, Maximilienne, Harpole, W. Stanley, Clark, Adam T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7713957/
https://www.ncbi.nlm.nih.gov/pubmed/33304536
http://dx.doi.org/10.1002/ece3.6926
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author Mühlbauer, Lina K.
Schulze, Maximilienne
Harpole, W. Stanley
Clark, Adam T.
author_facet Mühlbauer, Lina K.
Schulze, Maximilienne
Harpole, W. Stanley
Clark, Adam T.
author_sort Mühlbauer, Lina K.
collection PubMed
description Point 1: The ecological models of Alfred J. Lotka and Vito Volterra have had an enormous impact on ecology over the past century. Some of the earliest—and clearest—experimental tests of these models were famously conducted by Georgy Gause in the 1930s. Although well known, the data from these experiments are not widely available and are often difficult to analyze using standard statistical and computational tools. Point 2: Here, we introduce the gauseR package, a collection of tools for fitting Lotka‐Volterra models to time series data of one or more species. The package includes several methods for parameter estimation and optimization, and includes 42 datasets from Gause's species interaction experiments and related work. Additionally, we include with this paper a short blog post discussing the historical importance of these data and models, and an R vignette with a walk‐through introducing the package methods. The package is available for download at github.com/adamtclark/gauseR. Point 3: To demonstrate the package, we apply it to several classic experimental studies from Gause, as well as two other well‐known datasets on multi‐trophic dynamics on Isle Royale, and in spatially structured mite populations. In almost all cases, models fit observations closely and fitted parameter values make ecological sense. Point 4: Taken together, we hope that the methods, data, and analyses that we present here provide a simple and user‐friendly way to interact with complex ecological data. We are optimistic that these methods will be especially useful to students and educators who are studying ecological dynamics, as well as researchers who would like a fast tool for basic analyses.
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spelling pubmed-77139572020-12-09 gauseR: Simple methods for fitting Lotka‐Volterra models describing Gause’s “Struggle for Existence” Mühlbauer, Lina K. Schulze, Maximilienne Harpole, W. Stanley Clark, Adam T. Ecol Evol Original Research Point 1: The ecological models of Alfred J. Lotka and Vito Volterra have had an enormous impact on ecology over the past century. Some of the earliest—and clearest—experimental tests of these models were famously conducted by Georgy Gause in the 1930s. Although well known, the data from these experiments are not widely available and are often difficult to analyze using standard statistical and computational tools. Point 2: Here, we introduce the gauseR package, a collection of tools for fitting Lotka‐Volterra models to time series data of one or more species. The package includes several methods for parameter estimation and optimization, and includes 42 datasets from Gause's species interaction experiments and related work. Additionally, we include with this paper a short blog post discussing the historical importance of these data and models, and an R vignette with a walk‐through introducing the package methods. The package is available for download at github.com/adamtclark/gauseR. Point 3: To demonstrate the package, we apply it to several classic experimental studies from Gause, as well as two other well‐known datasets on multi‐trophic dynamics on Isle Royale, and in spatially structured mite populations. In almost all cases, models fit observations closely and fitted parameter values make ecological sense. Point 4: Taken together, we hope that the methods, data, and analyses that we present here provide a simple and user‐friendly way to interact with complex ecological data. We are optimistic that these methods will be especially useful to students and educators who are studying ecological dynamics, as well as researchers who would like a fast tool for basic analyses. John Wiley and Sons Inc. 2020-10-26 /pmc/articles/PMC7713957/ /pubmed/33304536 http://dx.doi.org/10.1002/ece3.6926 Text en © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Mühlbauer, Lina K.
Schulze, Maximilienne
Harpole, W. Stanley
Clark, Adam T.
gauseR: Simple methods for fitting Lotka‐Volterra models describing Gause’s “Struggle for Existence”
title gauseR: Simple methods for fitting Lotka‐Volterra models describing Gause’s “Struggle for Existence”
title_full gauseR: Simple methods for fitting Lotka‐Volterra models describing Gause’s “Struggle for Existence”
title_fullStr gauseR: Simple methods for fitting Lotka‐Volterra models describing Gause’s “Struggle for Existence”
title_full_unstemmed gauseR: Simple methods for fitting Lotka‐Volterra models describing Gause’s “Struggle for Existence”
title_short gauseR: Simple methods for fitting Lotka‐Volterra models describing Gause’s “Struggle for Existence”
title_sort gauser: simple methods for fitting lotka‐volterra models describing gause’s “struggle for existence”
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7713957/
https://www.ncbi.nlm.nih.gov/pubmed/33304536
http://dx.doi.org/10.1002/ece3.6926
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